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V5I1206 - Financial Intelligence Units (FIUs)
V5I0806 - Money Laundering: The Exception
V5I0406 - Network Monitoring
V5I0106 - Filing Compliance
V4I0405 - Terrorism Financing
V4I0305 - Telephone Toll Analysis
V4I0205 - Wire Transfers for Alien Smuggling
V4I0105 - Bust-out Schemes
V3I1204 - Structuring Financial Transactions
V3I1104 - Finished Intelligence (Proactive Analysis)
V3I1004 - Exposing Mortgage Fraud
V3I0904 - MIND Lab Integrates Course Data
V3I0804 - Suspicious SAR-MSB Filing Data
V3I0704 - Integrating Multiple Data Sources
V3I0604 - Analyzing Airline Profitability
V3I0504 - Corporate Fraud
V3I0404 - Employee Master File Analysis
V3I0304 - Prescription Fraud Patterns
V3I0204 - Social Network Analysis (SNA)
V3I0104 - Fraud Detection System (FDS)
V2I1203 - Integration with our Digital Information Gateway
V2I1103 - Financial Transactions Investigation
V2I1003 - Compliance Analysis
V2I0903 - Medical Insurance Claims Analysis
V2I0803 - Corporate Fraud Investigation
V2I0703 - Possible Domestic Terrorist Shooting
V2I0603 - Suspicious Activity Report (SAR) Filing
V2I0503 - Detecting Financial Crimes
V2I0403 - "Referential" Data Sources
V2I0303 - Proactive Analyses
V2I0203 - Transactional Activities
V2I0103 - Temporal Grid

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Referenced in our Newsletter Volume 3, Issue 4 - April 2004

Employee Master File Analysis

This month's review is focused on exposing different types of situations that potentially indicate fraud. Corporations of all sizes have issues covering all aspects of their operations including personnel, goods/services, and finance/accounting. The following examples show the types of patterns and analyses that are being performed to better understand vulnerabilities and financial exposure within a mid-sized company.

One of the datasets used in this example is based on the Employee Master File, which contains general information for all employees including their name, address, telephone number, and employment status. In the following diagram, the data was clustered within VisuaLinks based on the employment status field to show a total of 4 active groups.


The majority of the values were either "T" for terminated or "A" for active (icons in the chart were defined according to these values).

It was also noted there are 6 people with both "T" and "A" as their employment status - clearly, this is an anomaly and represents a control problem within the HR system. The single employee with a value of "L" is on leave from the company.

Using this information, the networks were expanded to bring in the addresses contained in the Employee Master File. The next diagram shows a high-level chart depicting this data with 291 employees and 281 addresses. In the upper-left part of this chart, it can be seen there are several employees sharing the same addresses.

Upon closer examination of the data, there are some relationships that raise concern with respect to active and terminated employees residing at the same address. The names and addresses in this next diagram are hidden with box-overlays to protect their privacy.
   The upper-left network shows an address with 3 employees (2 active, 1 terminated) where the last names are different; this represents a roommate situation and the company should be somewhat concerned about retention matters.

   The next network (second from left in top row) depicts 3 employees (1 active, 2 terminated) where all the last names are the same; the company should be very concerned with this situation regarding retention, moral, or possible theft.

   The lower-right network shows an active and terminated employee living at the same apartment complex; most likely there is no direct relationship between the employees and the company should not be concerned here.

Other diagrams using the phone numbers listed (e.g., home phone, emergency phone, etc) could also be used to expose commonality among the employees. Additional analyses can also show employee-as-vendor patterns based on shared characteristics such as addresses, phone, and fax numbers. When these types of situations are encountered and are not previously known, the company must review its internal controls for contract award, bid requirements, and vendor payment history to determine if fraud has been committed.



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